Platooning of Computational Resources in Automated Vehicles Networks

1. A system for platooning of computational resources, the system comprising: a vehicle tracker to: determine a first travel path along which a first on-board computational processor (OBCP) disposed in a first vehicle is predicted to travel during a time window; and identify a second OBCP as predicted to travel along a second travel path during at least a portion of the time window so as to be in ad hoc networking range of the first OBCP during at least the portion of the time window; and a platooning processor to: detect a platoonable task as one of a plurality of computational tasks predicted to consume at least a threshold amount of computational resources of the first OBCP during the time window; determine that the second OBCP is predicted to have available computational resources during at least the portion of the time window; schedule platooning of computational resources of the first OBCP and the second OBCP to perform the platoonable task; and instruct performance of the platoonable task by the first OBCP and the second OBCP in accordance with the scheduling.

2. The system of claim 1 , further comprising: a network processor to: establish communicative coupling of the first OBCP and the second OBCP via an ad hoc network upon arrival of at least the portion of the time window; and communicate instructions to at least one of the first OBCP or the second OBCP via the ad hoc network in accordance with the platooning processor instructing the performance of the platoonable task.

3. The system of claim 2 , wherein the platooning processor instructs the performance of the platoonable task responsive to detecting the network processor establishing the communicative coupling.

4. The system of claim 2 , further comprising: a back-end computational system remote from the first vehicle and comprising the network processor, the platooning processor, and the vehicle tracker.

5. The system of claim 1 , wherein determining the first travel path comprises: determining a first vehicle path along which the first vehicle is predicted to travel during the time window; and determining that the first OBCP is predicted to be disposed in the first vehicle during the time window, such that the first travel path of the first OBCP is coincident with the first vehicle path of the first vehicle during the time window.

6. The system of claim 5 , wherein identifying the second OBCP as predicted to travel along the second travel path comprises: determining a second vehicle path along which a second vehicle is predicted to travel during the time window; determining that the second OBCP is predicted to be disposed in the second vehicle during the time window, such that the second travel path of the second OBCP is coincident with the second vehicle path of the second vehicle during the time window; and determining that the second vehicle path places the second OBCP in ad hoc networking range of the first OBCP during at least the portion of the time window.

7. The system of claim 1 , wherein identifying the second OBCP as predicted to travel along the second travel path comprises predicting the second OBCP to be disposed in the first vehicle during at least the portion of the time window.

8. The system of claim 1 , wherein the first OBCP is structurally integrated in the first vehicle, and the second OBCP is integrated with a mobile device.

9. The system of claim 1 , wherein the platooning processor is further to: compute a computational resource demand for the time window according to an amount of the computational resources of the first OBCP predicted to be consumed by the plurality of computational tasks during the time window; and compute a computational resource supply for the time window according to an amount of the computational resources of the first OBCP predicted to be available for consumption by the plurality of computational tasks during the time window, such that the platooning processor is to detect the platoonable task responsive to determining that the computational resource demand for the time window exceeds the computational resource supply for the time window.

10. The system of claim 1 , wherein: the vehicle tracker is further to identify a set of candidate OBCPs as each predicted to travel along a respective travel path during at least the portion of the time window so as to be in ad hoc networking range of the first OBCP during at least the portion of the time window; and the platooning processor is to identify the second OBCP as being one of the set of candidate OBCPs predicted to have available computational resources during at least the portion of the time window.

11. The system of claim 1 , wherein: the platoonable task is executable as a plurality of parallel execution threads; and the platooning processor is to schedule the platooning by scheduling a first portion of the plurality of parallel execution threads to be executed by the first OBCP, and scheduling a second portion of the plurality of parallel execution threads to be executed by the second OBCP.

12. The system of claim 1 , wherein the first vehicle is an automated vehicle.

13. A method for platooning of computational resources, the method comprising: determining a first travel path along which a first on-board computational processor (OBCP) disposed in a first vehicle is predicted to travel during a time window; identifying a second OBCP as predicted to travel along a second travel path during at least a portion of the time window so as to be in ad hoc networking range of the first OBCP during at least the portion of the time window; detecting a platoonable task as one of a plurality of computational tasks predicted to consume at least a threshold amount of computational resources of the first OBCP during the time window; determining that the second OBCP is predicted to have available computational resources during at least the portion of the time window; scheduling platooning of computational resources of the first OBCP and the second OBCP to perform the platoonable task; and instructing performance of the platoonable task by the first OBCP and the second OBCP in accordance with the scheduling.

14. The method of claim 13 , further comprising: establishing communicative coupling of the first OBCP and the second OBCP via an ad hoc network upon arrival of at least the portion of the time window; and communicating instructions to at least one of the first OBCP or the second OBCP via the ad hoc network in accordance with the instructing the performance of the platoonable task.

15. The method of claim 13 , wherein determining the first travel path comprises: determining a first vehicle path along which the first vehicle is predicted to travel during the time window; and determining that the first OBCP is predicted to be disposed in the first vehicle during the time window, such that the first travel path of the first OBCP is coincident with the first vehicle path of the first vehicle during the time window.

16. The method of claim 15 , wherein identifying the second OBCP as predicted to travel along the second travel path comprises: determining a second vehicle path along which a second vehicle is predicted to travel during the time window; determining that the second OBCP is predicted to be disposed in the second vehicle during the time window, such that the second travel path of the second OBCP is coincident with the second vehicle path of the second vehicle during the time window; and determining that the second vehicle path places the second OBCP in ad hoc networking range of the first OBCP during at least the portion of the time window.

17. The method of claim 13 , wherein identifying the second OBCP as predicted to travel along the second travel path comprises predicting the second OBCP to be disposed in the first vehicle during at least the portion of the time window.

18. The method of claim 13 , wherein at least one of the first OBCP is and the second OBCP is integrated with a mobile device.

19. The method of claim 13 , further comprising: computing a computational resource demand for the time window according to an amount of the computational resources of the first OBCP predicted to be consumed by the plurality of computational tasks during the time window; and computing a computational resource supply for the time window according to an amount of the computational resources of the first OBCP predicted to be available for consumption by the plurality of computational tasks during the time window, such that the detecting the platoonable task is responsive to determining that the computational resource demand for the time window exceeds the computational resource supply for the time window.

20. The method of claim 13 , further comprising: identifying a set of candidate OBCPs as each predicted to travel along a respective travel path during at least the portion of the time window so as to be in ad hoc networking range of the first OBCP during at least the portion of the time window, wherein the determining that the second OBCP is predicted to have available computational resources during at least the portion of the time window comprises identifying the second OBCP as one of the set of candidate OBCPs predicted to have available computational resources during at least the portion of the time window.